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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/65869

    Title: 非線性像元分解考慮多次反射應用於高光譜影像;Nonlinear Unmixing with Multiple Reflection for Hyperspectral Remote Sensing Imagery
    Authors: 徐世珉;Syu,Shin-Min
    Contributors: 遙測科技碩士學位學程
    Keywords: 高光譜;非線性像元分解;改進的廣義雙線性模型;Hyperspectral Images;Nonlinear Unmixing;Modified Generalized Bilinear Model.
    Date: 2014-07-30
    Issue Date: 2014-10-15 17:16:12 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 遙測是指在衛星上或飛機上測量地表資訊而不需要接觸到目標。近年遙測科技蓬勃發展,而高光譜影像為遙測影像中重要的產品,它能同時利用許多感應器用來紀錄不同波段的電磁波能量值,它的光譜數量可以到達數百或數千個波段,因為高光譜有著很高的光譜解析率,所以可以分辨目標物的細微不同。
    ;Remote sensing is to measure the object properties on the earth’s surface using data acquire from aircrafts and satellites. Hyperspectral imaging spectrometers record electromagnetic energy scattered in their instantaneous field of view with hundreds or thousands of spectral channels. This high spectral resolution improves the capability for material identification via spectroscopic analysis.
    However, because of spatial resolution, each pixel in hyperspectral images usually contains more than one material. Linear mixture model (LMM) is developed for this problem and has been widely studied. This model assumes that the spectrum of a pixel is linearly combined by all the resident materials with their corresponding abundance, and it ignores the reflection between materials. Nonlinear models have recently drawn lots of attentions for spectral unmixing. The generalized bilinear model (GBM) has been proposed for nonlinear mixture which considers the second order interactions between two different endmembers. However, it neglects the possibility of second order interactions between the same endmembers. In this study, we propose a modified GBM (MGBM) by considering second order reflection between all the endmembers. The non-negativity and sum-to-one constraints for the abundances are ensured by the proposed algorithms.
    Appears in Collections:[遙測科技碩士學位學程] 博碩士論文

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